1. Technical Field
The present invention generally relates to determining physical network topology of heterogeneous networks and in particular to determining physical network topology without employing vendor-dependent information for network devices. Still more particularly, the present invention relates to employing neural networks to generically classify and physically group network devices based on communications parameters from a selected network device including round trip time, bottleneck link speed and hop count.
2. Description of the Related Art
Computer networks are essential features of contemporary computing, providing the framework for exchange of data and execution of distributed applications, either through client-server interaction such as HyperText Transmission Protocol clients and servers or collaborative operation such as failover redundancy in highly available networks. In order to efficiently perform tasks, most networking and system management applications today require a knowledge of the underlying physical network topology. However, existing topology applications provide, at best, only an approximation of the actual physical topology.
A variety of different reasons contribute to the use of approximations for network physical topologies in contemporary applications. The primary reason, however, is that a substantial number of network devices (e.g., network interface cards or adapters) do not implement any functions or variables which would allow those network devices to be xe2x80x9cdiscoveredxe2x80x9d or automatically identified and/or classified by a topology application. Even when functions or variables are implemented by a network device to provide information to topology applications, the information is provided in a manufacturer-dependent, and often private, manner.
Currently, the most common technique utilized by topology applications to discover physical topology involves extracting topology information from each individual network device within the network utilizing the Simple Network Management Protocol (SNMP). This is not a simple task because, as noted above, no standard exists across different manufacturers or vendors for organizing or classifying physical network topology information. For example, Cisco Systems may employ a particular data structure to describe the connection to their devices while 3COM Corporation employs an entirely different data structure, which may or may not include all of the same variables as the Cisco data structure, to describe their connection.
It would be desirable, therefore, to be able to determine physical network topology without knowing or utilizing any vendor-specific information. It would further be advantageous to employ physical topology information which relies only on information which is readily available within any heterogeneous network.
It is therefore one object of the present invention to provide an improved method, apparatus, and computer program product for determining physical network topology of heterogeneous networks.
It is another object of the present invention to provide a method, apparatus, and computer program product for determining physical network topology without employing vendor-dependent information for network devices.
It is yet another object of the present invention to employ neural networks to generically classify and physically group network devices based on communications parameters from a selected network device including round trip time, bottleneck link speed and hop count.
The foregoing objects are achieved as is now described. Round trip time, bottleneck link speed, and hop count information from one node to the remaining nodes within a network is collected and processed by an adaptive resonance theory (ART) neural network to classify the nodes by physical location or site group. For each site group, round trip time from one node to the remaining nodes is then collected and processed utilizing an ART neural network to classify the nodes into one or more physical groups. The resulting breakdown of site groups within the network and physical groups within the site groups forms a model which may be employed by networking and system management applications. No private or proprietary vendor specific information from communications devices within the network need be employed to develop the model, only publicly available information regarding communications parameters.
The above as well as additional objectives, features, and advantages of the present invention will become apparent in the following detailed written description.